TDengine Concepts: Data Model

Although TDengine is a time-series database (TSDB), it uses a data model with which you may be familiar from relational databases. Before you start storing your data in TDengine, you design the how your data will be structured – including databases, supertables, and subtables.

Create a Database

All tables and data in your environment are stored in a database. In TDengine, you generally create a separate database for each group of devices whose data has different characteristics. This way you can configure each database in the optimal manner for the data it contains.

TDengine provides a variety of parameters that extend standard SQL for database creation. For example, consider the following SQL statement:

CREATE DATABASE meters KEEP 365 DAYS 10 BLOCKS 4 UPDATE 1;

This statement creates a database named meters with the following parameters:

  1. KEEP 365 indicates that data is retained for 365 days, after which it is automatically deleted.
  2. DAYS 10 indicates that each data file stores 10 days of data.
  3. BLOCKS 4 indicates that the database has four memory blocks for data updating.

With these extensions, you can create databases that align with the storage strategy for your data. For a complete overview of database parameters, see Database.

After you have created a database, run the USE statement to switch to it.

USE meters;

Replace the database operating in the current connection with “power”, otherwise, before operating on a specific table, you need to use “database name. table name” to specify the name of database to use.

Note:

  • Any table or supertable belongs to a database. Before creating a table, a database must be created first.
  • Tables in two different databases cannot be JOIN.

Create a Supertable

An IoT system often has many types of devices, such as smart meters, transformers, buses, switches, etc. for power grids. In order to facilitate aggregation among multiple tables, using TDengine, it is necessary to create a STable for each type of data collection point. Taking the smart meter in Table 1 as an example, you can use the following SQL command to create a STable:

CREATE STABLE meters (ts timestamp, current float, voltage int, phase float) TAGS (location binary(64), groupId int);

Note: The STABLE keyword in this instruction needs to be written as TABLE in versions before 2.0.15.

Just like creating an ordinary table, you need to provide the table name (‘meters’ in the example) and the table structure Schema, that is, the definition of data columns. The first column must be a timestamp (‘ts’ in the example), the other columns are the physical metrics collected (current, volume, phase in the example), and the data types can be int, float, string, etc. In addition, you need to provide the schema of the tag (location, groupId in the example), and the data types of the tag can be int, float, string and so on. Static attributes of collection points can often be used as tags, such as geographic location of collection points, device model, device group ID, administrator ID, etc. The schema of the tag can be added, deleted and modified afterwards. Please refer to the STable Management section of TAOS SQL for specific definitions and details.

Each type of data collection point needs an established STable, so an IoT system often has multiple STables. For the power grid, we need to build a STable for smart meters, transformers, buses, switches, etc. For IoT, a device may have multiple data collection points (for example, a fan for wind-driven generator, some collection points capture parameters such as current and voltage, and some capture environmental parameters such as temperature, humidity and wind direction). In this case, multiple STables need to be established for corresponding types of devices. All collected physical metrics contained in one and the same STable must be collected at the same time (with a consistent timestamp).

A STable allows up to 1024 columns. If the number of physical metrics collected at a collection point exceeds 1024, multiple STables need to be built to process them. A system can have multiple DBs, and a DB can have one or more STables.

Create a Table

TDengine builds a table independently for each data collection point. Similar to standard relational data, one table has a table name, Schema, but in addition, it can also carry one or more tags. When creating, you need to use the STable as a template and specify the specific value of the tag. Taking the smart meter in Table 1 as an example, the following SQL command can be used to build the table:

CREATE TABLE d1001 USING meters TAGS ("Beijing.Chaoyang", 2);

Where d1001 is the table name, meters is the name of the STable, followed by the specific tag value of tag Location as “Beijing.Chaoyang”, and the specific tag value of tag groupId 2. Although the tag value needs to be specified when creating the table, it can be modified afterwards. Please refer to the Table Management section of TAOS SQL for details.

Note: At present, TDengine does not technically restrict the use of a STable of a database (dbA) as a template to create a sub-table of another database (dbB). This usage will be prohibited later, and it is not recommended to use this method to create a table.

TDengine suggests to use the globally unique ID of data collection point as a table name (such as device serial number). However, in some scenarios, there is no unique ID, and multiple IDs can be combined into a unique ID. It is not recommended to use a unique ID as tag value.

Automatic table creating: In some special scenarios, user is not sure whether the table of a certain data collection point exists when writing data. In this case, the non-existent table can be created by using automatic table building syntax when writing data. If the table already exists, no new table will be created. For example:

INSERT INTO d1001 USING METERS TAGS ("Beijng.Chaoyang", 2) VALUES (now, 10.2, 219, 0.32);

The SQL statement above inserts records (now, 10.2, 219, 0.32) into table d1001. If table d1001 has not been created yet, the STable meters is used as the template to automatically create it, and the tag value “Beijing.Chaoyang”, 2 is marked at the same time.

For detailed syntax of automatic table building, please refer to the “Automatic Table Creation When Inserting Records” section.

Multi-column Model vs Single-column Model

TDengine supports multi-column model. As long as physical metrics are collected simultaneously by a data collection point (with a consistent timestamp), these metrics can be placed in a STable as different columns. However, there is also an extreme design, a single-column model, in which each collected physical metric is set up separately, so each type of physical metrics is set up separately with a STable. For example, create 3 Stables, one each for current, voltage and phase.

TDengine recommends using multi-column model as much as possible because of higher insertion and storage efficiency. However, for some scenarios, types of collected metrics often change. In this case, if multi-column model is adopted, the structure definition of STable needs to be frequently modified so make the application complicated. To avoid that, single-column model is recommended.